Why should the baseline's prediction be near zero, according to the Integrated Gradients paper?
You are right that the baseline score is near zero only when there are a large number of label classes, i.e., when k is large. We should have qualified this line in the paper more carefully.
In this sense, formally, the technique explains the *difference in prediction between the input score and the baseline score, as is made clear elsewhere in the paper (see Remark 1 and Proposition 1 for instance.)